Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers

Human Brain Mapping
Yael JacobAvner Thaler

Abstract

Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group for future development of Parkinson's disease (PD) and have demonstrated task related fMRI changes. However, resting-state networks have received less research focus, thus this study aimed to assess the integrity of the motor, default mode (DMN), salience (SAL), and dorsal attention (DAN) networks among this unique population by using two different connectivity measures: interregional functional connectivity analysis and Dependency network analysis (DEP NA). Machine learning classification methods were used to distinguish connectivity between the two groups of participants. Forty-four NMC and 41 non-manifesting non-carriers (NMNC) participated in this study; while no behavioral differences on standard questionnaires could be detected, NMC demonstrated lower connectivity measures in the DMN, SAL, and DAN compared to NMNC but not in the motor network. Significant correlations between NMC connectivity measures in the SAL and attention were identified. Machine learning classification separated NMC from NMNC with an accuracy rate above 0.8. Reduced integrity of non-motor networks was detected among NMC of the G2019S mutation in the L...Continue Reading

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Citations

Jan 7, 2020·NeuroImage. Clinical·Yael JacobPriti Balchandani
Jan 27, 2021·International Journal of Molecular Sciences·Vinita G Chittoor-VinodBirgitt Schüle
Apr 6, 2021·Current Neurology and Neuroscience Reports·Sule Tinaz
Sep 18, 2021·Molecular Medicine·Sanne K MelesKlaus L Leenders

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